Biomedical subjects

M P Becker

Publications and source records attributed to M P Becker.

At least 19 recordsLinked to original sources

PubMed1999

Reliability of nerve conduction studies among active workers.

Nerve conduction studies play an important role in clinical practice and research. Given their widespread use, reliability of tests merits careful attention. We assessed interexaminer and intraexaminer reliability of median and ulnar sensory nerve measures of amplitude, onset latency, and peak latency. In a two-phase cross-sectional study, two examiners tested 158 workers. Reliability was assessed with intraclass correlations (ICC) and kappa statistics. Median nerve measures were more reliable (ICC range, 0.76 to 0.92) than ulnar measures (ICC range, 0.22 to 0.85). Ulnar-onset latencies had the worst reliability. The median-ulnar peak latency difference was a particularly stable measure (ICC range, 0.79 to 0.92). The median-ulnar peak latency difference had high interexaminer reliability (kappa range, 0.71 to 0.79) for normal tests defined by cut points of 0.8 ms and 0.5 ms. Intraexaminer reliability was higher with the 0.8-ms cut point (kappa = 0.90 and kappa = 0.85 for examiners 1 and 2, respectively). Rather than absolute cut points to describe normality, a more rational interpretation of results can be made with ordered categories or continuous measures.

Adult↗

PubMed1999

Diabetes and pregnancy. Preconception care, pregnancy outcomes, resource utilization and costs.

OBJECTIVE: To describe and compare pregnancy outcomes, resource utilization and costs among women with diabetes who receive and do not receive preconception care. STUDY DESIGN: A multicenter, prospective, observational study of women with type 1 diabetes who received preconception care (PC), became pregnant and delivered (PC women) and women with type 1 diabetes who received prenatal care (PC) only and delivered (PN women). RESULTS: As compared to PN women (n = 74), PC women (n = 24) were seen earlier in gestation and had significantly lower glycosylated hemoglobin levels. The combined number of outpatient visits for PC women was not greater than for PN women. PC women were hospitalized significantly less during pregnancy and tended to have shorter inpatient stays. The mean length of stay after delivery was significantly shorter for PC women. Intensity of care tended to be lower and length of stay shorter for infants of mothers who received PC care. The net cost saving associated with PC care was approximately $34,000 per patient. CONCLUSION: PC achieves its major intended health benefits and is associated with reduced resource utilization and substantially reduced costs. For both health and economic reasons, clinical practice and public policy should embrace PC.

Adult↗

PubMed1998

Increased efficiency of analyses: cumulative logistic regression vs ordinary logistic regression.

The common practice of collapsing inherently continuous or ordinal variables into two categories causes information loss that may potentially weaken power to detect effects of explanatory variables and result in Type II errors in statistical inference. The purpose of this investigation was to illustrate, using a substantive example, the potential increase in power gained from an ordinal instead of a dichotomous specification for an inherently continuous response. Ordinary (OLR) and cumulative logistic regression (CLR) modeling were used to test the hypothesis that the risk of alveolar bone loss over 2 years is greater for subjects with poorer control of non-insulin-dependent diabetes mellitus (NIDDM) than for those who do not have diabetes or have better controlled NIDDM. There were 359 subjects; 21 of whom had NIDDM. Analysis of main effects using OLR for the dichotomous outcome (no change in radiographic bone loss vs any change) produced parameter estimates for better control and poorer control that were not statistically significant. CLR analysis of main effects using a 4-category ordinal specification for radiographic bone loss also produced a parameter estimate for better control that was not statistically significant, but which estimated poorer control to have a significant effect. The fit of this CLR model was significantly better at P < 0.05 than that for the OLR. While an OLR model testing the interaction between age and control status did not converge after 100 iterations, the CLR interaction model converged without difficulty and estimated a significant effect for interaction between age and poorer control. Results from the CLR analysis, in contrast to the OLR model, would lead one to conclude that the risk for more severe bone loss progression after 2 years is greater in subjects with poorer controlled NIDDM and that subjects with better controlled NIDDM may not have greater risk of bone loss progression than those without diabetes. The use of an ordinal instead of a dichotomous specification for an inherently continuous response provided increased power, more precise parameter estimates, and a significantly better fitting model. In estimating parameter estimates for odds ratios or risks, it is important to consider using ordinal logistic regression where the response is inherently continuous or ordinal.

Adolescent↗

PubMed1998

Glycemic control and alveolar bone loss progression in type 2 diabetes.

This study tested the hypothesis that the risk for alveolar bone loss is greater, and bone loss progression more severe, for subjects with poorly controlled (PC) type 2 diabetes mellitus (type 2 DM) compared to those without type 2 DM or with better controlled (BC) type 2 DM. The PC group had glycosylated hemoglobin (HbA1) > or = 9%; the BC group had HbA1 < 9%. Data from the longitudinal study of the oral health of residents of the Gila River Indian Community were analyzed. Of the 359 subjects, aged 15 to 57 with less than 25% radiographic bone loss at baseline, 338 did not have type 2 DM, 14 were BC, and 7 were PC. Panoramic radiographs were used to assess interproximal bone level. Bone scores (scale 0-4) corresponding to bone loss of 0%, 1% to 24%, 25% to 49%, 50% to 74%, or > or = 75% were used to identify the worst bone score (WBS) in the dentition. Change in worst bone score at follow-up, the outcome, was specified on a 4-category ordinal scale as no change, or a 1-, 2-, 3-, or 4-category increase over baseline WBS (WBS1). Poorly controlled diabetes, age, calculus, time to follow-up examination, and WBS1 were statistically significant explanatory variables in ordinal logistic regression models. Poorly controlled type 2 DM was positively associated with greater risk for a change in bone score (compared to subjects without type 2 DM) when the covariates were included in the model. The cumulative odds ratio (COR) at each threshold of the ordered response was 11.4 (95% CI = 2.5, 53.3). When contrasted with subjects with BC type 2 DM, the COR for those in the PC group was 5.3 (95% CI = 0.8, 53.3). The COR for subjects with BC type 2 DM was 2.2 (95% CI = 0.7, 6.5), when contrasted to those without type 2 DM. These results suggest that poorer glycemic control leads to both an increased risk for alveolar bone loss and more severe progression over those without type 2 DM, and that there may be a gradient, with the risk for bone loss progression for those with better controlled type 2 DM intermediate to the other 2 groups.

Adolescent↗

PubMed1998

Non-insulin dependent diabetes mellitus and alveolar bone loss progression over 2 years.

This study tested the hypothesis that persons with non-insulin dependent diabetes mellitus (NIDDM) have greater risk of more severe alveolar bone loss progression over a 2-year period than those without NIDDM. Data from the longitudinal study of the oral health of residents of the Gila River Indian Community were analyzed for 362 subjects, aged 15 to 57, 338 of whom had less than 25% radiographic bone loss at baseline, and who did not develop NIDDM nor lose any teeth during the 2-year study period. The other 24 subjects had NIDDM at baseline, but met the other selection criteria. Bone scores (scale 0-4) from panoramic radiographs corresponded to bone loss of 0%, 1%-24%, 25%-49%, 50%-74%, or 75% and greater. Change in bone score category was computed as the change in worst bone score (WBS) reading after 2 years. Age, calculus, NIDDM status, time to follow-up examination, and baseline WBS were explanatory variables in regression models for ordinal categorical response variables. NIDDM was positively associated with the probability of a change in bone score when the covariates were controlled. The cumulative odds ratio for NIDDM at each threshold of the ordered response was 4.23 (95% C.I. = 1.80, 9.92). In addition to being associated with the incidence of alveolar bone loss (as demonstrated in previous studies), these results suggest an NIDDM-associated increased rate of alveolar bone loss progression.

Adolescent↗

PubMed1997

Psyllium-enriched cereals lower blood total cholesterol and LDL cholesterol, but not HDL cholesterol, in hypercholesterolemic adults: results of a meta-analysis.

We conducted a meta-analysis to determine the effect of consumption of psyllium-enriched cereal products on blood total cholesterol (TC), LDL cholesterol (LDL-C) and HDL cholesterol (HDL-C) levels and to estimate the magnitude of the effect among 404 adults with mild to moderate hypercholesterolemia (TC of 5.17-7.8 mmol/L) who consumed a low fat diet. Studies of psyllium cereals were identified by a computerized search of MEDLINE and Current Contents and by contacting United States-based food companies involved in psyllium research. Published and unpublished studies were reviewed by one author and considered eligible for inclusion in the meta-analysis if they were conducted in humans, were randomized, controlled experiments, and included a control group that ate cereal providing </=3 g soluble fiber/d. Eight published and four unpublished studies, conducted in four countries, met the criteria. Analysis of a linear model was performed, controlling for sex and age. Female subjects were divided into two groups to provide a rough estimate of the effect of menopausal status (premenopausal = <50 y, postmenopausal = >/=50 y) on blood lipids. The meta-analysis showed that subjects who consumed a psyllium cereal had lower TC and LDL-C concentrations [differences of 0.31 mmol/L (5%) and 0.35 mmol/L (9%), respectively] than subjects who ate a control cereal; HDL-C concentrations were unaffected in subjects eating psyllium cereal. There was no effect of sex, age or menopausal status on blood lipids. Results indicate that consuming a psyllium-enriched cereal as part of a low fat diet improves the blood lipid profile of hypercholesterolemic adults over that which can be achieved with a low fat diet alone.

Adult↗

PubMed1997

EM algorithms without missing data.

Most problems in computational statistics involve optimization of an objective function such as a loglikelihood, a sum of squares, or a log posterior function. The EM algorithm is one of the most effective algorithms for maximization because it iteratively transfers maximization from a complex function to a simple, surrogate function. This theoretical perspective clarifies the operation of the EM algorithm and suggests novel generalizations. Besides simplifying maximization, optimization transfer usually leads to highly stable algorithms with well-understood local and global convergence properties. Although convergence can be excruciatingly slow, various devices exist for accelerating it. Beginning with the EM algorithm, we review in this paper several optimization transfer algorithms of substantial utility in medical statistics.

Algorithms↗

PubMed1997

Latent variable modeling of diagnostic accuracy.

Latent class analysis has been applied in medical research to assessing the sensitivity and specificity of diagnostic tests/diagnosticians. In these applications, a dichotomous latent variable corresponding to the unobserved true disease status of the patients is assumed. Associations among multiple diagnostic tests are attributed to the unobserved heterogeneity induced by the latent variable, and inferences for the sensitivities and specificities of the diagnostic tests are made possible even though the true disease status is unknown. However, a shortcoming of this approach to analyses of diagnostic tests is that the standard assumption of conditional independence among the diagnostic tests given a latent class is contraindicated by the data in some applications. In the present paper, models incorporating dependence among the diagnostic tests given a latent class are proposed. The models are parameterized so that the sensitivities and specificities of the diagnostic tests are simple functions of model parameters, and the usual latent class model obtains as a special case. Marginal models are used to account for the dependencies within each latent class. An accelerated EM gradient algorithm is demonstrated to obtain maximum likelihood estimates of the parameters of interest, as well as estimates of the precision of the estimates.

Analysis of Variance↗

PubMed1996

Severe periodontitis and risk for poor glycemic control in patients with non-insulin-dependent diabetes mellitus.

This study tested the hypothesis that severe periodontitis in persons with non-insulin-dependent diabetes mellitus (NIDDM) increases the risk of poor glycemic control. Data from the longitudinal study of residents of the Gila River Indian Community were analyzed for dentate subjects aged 18 to 67, comprising all those: 1) diagnosed at baseline with NIDDM (at least 200 mg/dL plasma glucose after a 2-hour oral glucose tolerance test); 2) with baseline glycosylated hemoglobin (HbA1) less than 9%; and 3) who remained dentate during the 2-year follow-up period. Medical and dental examinations were conducted at 2-year intervals. Severe periodontitis was specified two ways for separate analyses: 1) as baseline periodontal attachment loss of 6 mm or more on at least one index tooth; and 2) baseline radiographic bone loss of 50% or more on at least one tooth. Clinical data for loss of periodontal attachment were available for 80 subjects who had at least one follow-up examination, 9 of whom had two follow-up examinations at 2-year intervals after baseline. Radiographic bone loss data were available for 88 subjects who had at least one follow-up examination, 17 of whom had two follow-up examinations. Poor glycemic control was specified as the presence of HbA, of 9% or more at follow-up. To increase the sample size, observations from baseline to second examination and from second to third examinations were combined. To control for non-independence of observations, generalized estimating equations (GEE) were used for regression modeling. Severe periodontitis at baseline was associated with increased risk of poor glycemic control at follow-up. Other statistically significant covariates in the GEE models were: 1) baseline age; 2) level of glycemic control at baseline; 3) having more severe NIDDM at baseline; 4) duration of NIDDM; and 5) smoking at baseline. These results support considering severe periodontitis as a risk factor for poor glycemic control and suggest that physicians treating patients with NIDDM should be alert to the signs of severe periodontitis in managing NIDDM.

Adolescent↗

PubMed1995

Diabetes and pregnancy. Factors associated with seeking pre-conception care.

OBJECTIVE: To define sociodemographic characteristics, medical factors, knowledge, attitudes, and health-related behaviors that distinguish women with established diabetes who seek pre-conception care from those who seek care only after conception. RESEARCH DESIGN AND METHODS: A multicenter, case-control study of women with established diabetes making their first pre-conception visit (n = 57) or first prenatal visit without having received pre-conception care (n = 97). RESULTS: Pre-conception subjects were significantly more likely to be married (93 vs. 51%), living with their partners (93 vs. 60%), and employed (78 vs. 41%); to have higher levels of education (73% beyond high school vs. 41%) and income (86% > $20,000 vs. 60%); and to have insulin-dependent diabetes mellitus (IDDM) (93 vs. 81%). Pre-conception subjects with IDDM were more likely to have discussed pre-conception care with their health care providers (98 vs. 51%) and to have been encouraged to get it (77 vs. 43%). In the prenatal group, only 24% of pregnancies were planned. Pre-conception patients were more knowledgeable about diabetes, perceived greater benefits of pre-conception care, and received more instrumental support. CONCLUSIONS: Only about one-third of women with established diabetes receive pre-conception care. Interventions must address prevention of unintended pregnancy. Providers must regard every visit with a diabetic woman as a pre-conception visit. Contraception must be explicitly discussed, and pregnancies should be planned. In counseling, the benefits of pre-conception care should be stressed and the support of families and friends should be elicited.

Adult↗

PubMed1995

Multivariate contingency tables and the analysis of exchangeability.

There are settings in the social and health sciences where it is natural to question whether a collection of discrete random variables is exchangeable. In this paper the inter-relationships between parameter symmetry, parameter invariance, and exchangeable discrete random variables are investigated within the log-linear models framework. We demonstrate how log-linear models can be used to formulate and test hypotheses of various forms of exchangeability, and to characterize departures from exchangeability. Conditions under which the observed cross-classification collapses into a lower dimensional cross-classification, while preserving the essential probability structure of the higher dimensional cross-classification, and the model structure of this lower dimensional cross-classification are presented. The development is sufficiently general to allow for subsetting the variables into classes, which is important for some applications. For example, in studying the spatial clustering of periodontal disease, there is interest in studying differences among disease patterns between the upper and lower arches in terms of parameter symmetry, parameter invariance, and exchangeability. Cross-sectional periodontal disease data from a study of Pima Indians residing in the Gila River Indian Community are used to illustrate how log-linear models may be used to examine for exchangeability, and for specific departures from exchangeability.

Adolescent↗

PubMed1994

Physician decision making and variation in hospital admission rates for suspected acute cardiac ischemia. A tale of two towns.

The authors tested the "uncertainty hypothesis," which holds that variations in rates of hospitalization or surgeries across small geographic areas reflect differences in physicians' decision making when confronting uncertainty. A small-areas variation analysis of suspected acute cardiac ischemia (ACI) admissions in northern Michigan was performed, and two demographically nearly identical towns differing by a factor of 3 in ACI admission rates were selected. Medical records of all patients evaluated in the emergency departments of these hospitals for suspected ACI in 1988 were abstracted retrospectively. Probabilities of ACI were objectively estimated using the Acute Cardiac Ischemia Time-Insensitive Predictive Instrument. Logistic regression of admission on patient characteristics, other illnesses, probability of ACI, and community revealed no difference in admission decisions between the two hospitals (odds ratio for community = 0.766, 95% confidence interval, 0.542-1.08, n = 787, P > .1). Nearly twice as many patients with ACI presented to the emergency department of the high-admitting hospital as to the low-admitting hospital. The authors conclude that, at least for ACI, population-based area discharge rates do not necessarily reflect case-based decision rates. Drawing inferences regarding physician decision making from discharge or claims datasets may lead to error.

Acute Disease↗

PubMed1993

Marginal modeling of binary cross-over data.

A model specified in terms of linear models for marginal logits and linear models for log-odds ratios is proposed for the analysis of two-period binary cross-over experiments. Hypothesis testing and parameter estimation are facilitated by standard likelihood methodology. Two examples are used to illustrate how the model can be used to analyze two-period binary cross-over experiments. Results from a simulation study demonstrate that this approach to the analysis of binary cross-over data compares favorably with standard procedures, such as the Mainland-Gart test for a treatment difference, Prescott's test for a treatment difference, and the Hills-Armitage test for treatment-by-period interaction.

Biometry↗

PubMed1992

Log-linear modelling of pairwise interobserver agreement on a categorical scale.

This article uses log-linear models to describe pairwise agreement among several raters who classify a sample on a subjective categorical scale. The models describe agreement structure simultaneously for second-order marginal tables of a multidimensional cross-classification of ratings. Practical difficulties arise in fitting the models, because models refer to pairwise marginal tables of a very large and sparse table. A standard analysis that treats the marginal tables as independent yields consistent estimates of model parameters, but not of the covariance matrix of the estimates. We estimate the covariance matrix using the jackknife. We apply the models to describe agreement between evaluations made by seven pathologists of carcinoma in situ of the uterine cervix, using a five-level ordinal scale. Previous analyses showed differences among the pathologists in their pairwise levels of agreement, but we observe near homogeneity in the dependence structure of their ratings.

Carcinoma in Situ↗

PubMed1992

Rural motor vehicle crash mortality: the role of crash severity and medical resources.

We did a retrospective case control study to examine the relationship between the risk of dying for Michigan motor vehicle crash (MVC) drivers and the type of county (rural/nonrural) of crash occurrence, while adjusting for crash characteristics, age, sex, and the medical resources in the county of crash occurrence. The 1987 Michigan Accident Census was used to obtain data regarding all MVC driver nonsurvivors (733) and a random sample of all surviving drivers (2,483). County of crash occurrence was defined as rural or nonrural. The crash characteristics analyzed were vehicle deformity, seat belt use, and drivability of the vehicle from the scene. Age and sex of the driver were also analyzed. Medical resource characteristics for the county of crash occurrence were measured as the number of resources per square mile for each of the following: ambulances, emergency medical technicians (EMT), acute care hospital beds, and operating rooms, surgeons and emergency physicians. Also considered were the number and level of emergency rooms in the county of crash occurrence along with the maximum level of prehospital care available (basic life support versus advanced life support) in a county. Before adjusting, the relative risk (RR) for rural MVC drivers dying, compared to their nonrural counterparts, was 1.96. Adjustment for crash characteristics, age, and sex (using logistic regression) decreased the RR to 1.51. An attempt to add medical resource variables to the model resulted in high correlation with the rural/nonrural variable, as well as with each other. This multi-collinearity prevented us from providing a simple explanation of the role of medical resource variables as predictors of survival.(ABSTRACT TRUNCATED AT 250 WORDS)

Accidents, Traffic↗

PubMed1992

Nursing care requirements of patients with DNR orders in intensive care units.

The purpose of this study was to examine the differences in demographic characteristics and nursing care requirements of patients with and patients without DNR (do not resuscitate) orders in intensive care. The sample consisted of 62 patients with and 62 without DNR orders from the intensive care units of three community hospitals. Data were collected until patients recovered and were transferred from the unit or until death occurred. Data were analyzed by chi-square tests for homogeneity, t tests, and analysis of covariance. Patients with DNR orders were white (p = 0.015), older (p = 0.03), more likely to reside in nursing homes (p = 0.04), had longer intensive care stays (p = 0.0005), were more likely to be admitted from another nursing unit (p less than 0.001), and had higher mortality rates (p less than 0.001). In intensive care settings, patients with DNR orders received more nursing care than patients who did not have DNR orders.

Adult↗

PubMed1991

Preliminary development of two predictive models for DNR patients in intensive care.

The purpose of this study was to identify which variables are the best predictors of a do-not-resuscitate (DNR) classification and develop a model to predict the nursing care required by DNR patients in the ICU. Data collected on DNR and non-DNR patients included nursing care requirements, severity of illness, resource allocation and sociodemographic characteristics. One model identified the best predictors of a DNR classification in intensive care as the origin of admission and the severity of illness score on the day of admission to intensive care. The second model identified the best predictors of nursing care requirements for DNR patients in intensive care as the number of days spent in intensive care prior to the DNR order, the average daily resource allocation points after the DNR order, and the severity of illness score on the day the DNR order was designated.

Aged↗

PubMed1989

Using association models to analyse agreement data: two examples.

Two examples demonstrate how one can use association models to analyse agreement data. The first example concerns intra-rater variability in the classification of sputum cytology slides, and the second deals with variability associated with the reporting of passive smoking histories. The paper emphasizes models in which one estimates category scores from the data, that is models that are not in the log-linear family of models. Such models have use in assessment of category distinguishability and provide insights not easily obtained with log-linear models.

Case-Control Studies↗